class_docstr: Random augment with fixed magnitude.
class_docstr_tok: ["Random","augment","with","fixed","magnitude","."]
code: def __call__(self, image):
      aug_image = image
      for _ in range(self.n):
          aug_image = self._pick_and_apply_augmentation(aug_image)
      return aug_image
  
file_path: objax/examples/fixmatch/libml/augment/randaugment/randaugment.py
imports: from typing import Optional
  import tensorflow
  from examples.fixmatch.libml.augment.randaugment import augment_ops
label_desc: Use image node_id 4 for calling the RandAugment obj's underlying member method code with example usage: obj.__call__(image) and returns: aug_image